IJACSA Volume 3 Issue 7

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Abstract: In this paper, we report the results of new experiments that test the performance of Scala parallel collections to find the fair value of riskless bond portfolios using commodity multicore platforms. We developed four algorithms, each of two kinds in Scala and ran them for one to 1024 portfolios, each with a variable number of bonds with daily to yearly cash flows and 1 year to 30 year. We ran each algorithm 11 times at each workload size on three different multicore platforms. We systematically observed the differences and tested them for statistical significance. All the parallel algorithms exhibited super-linear speedup and super-efficiency consistent with maximum performance expectations for scientific computing workloads. The first-order effort or “naïve” parallel algorithms were easiest to write since they followed directly from the serial algorithms. We found we could improve upon the naïve approach with second-order efforts, namely, fine-grain parallel algorithms, which showed the overall best, statistically significant performance, followed by coarse-grain algorithms. To our knowledge these results have not been presented elsewhere.

Abstract: In this article we study approaches that can be used to minimise the convergence time, we also make a focus on microloops phenomenon, analysis and means to mitigate them. The convergence time reflects the time required by a network to react to a failure of a link or a router failure itself. When all nodes (routers) have updated their respective routing and forwarding databases, we can say the network has converged. This study will help in building real-time and resilient network infrastructure, the goal is to make any evenement in the core network, as transparent as possible to any sensitive and real-time flows. This study is also, a deepening of earlier works presented in [10] and [11].

Abstract: Singular Value Decomposition (SVD) has recently emerged as a new paradigm for processing different types of images. SVD is an attractive algebraic transform for image processing applications. The paper proposes an experimental survey for the SVD as an efficient transform in image processing applications. Despite the well known fact that SVD offers attractive properties in imaging, the exploring of using its properties in various image applications is currently at its infancy. Since the SVD has many attractive properties have not been utilized, this paper contributes in using these generous properties in newly image applications and gives a highly recommendation for more research challenges. In this paper, the SVD properties for images are experimentally presented to be utilized in developing new SVD-based image processing applications. The paper offers survey on the developed SVD based image applications. The paper also proposes some new contributions that were originated from SVD properties analysis in different image processing. The aim of this paper is to provide a better understanding of the SVD in image processing and identify important various applications and open research directions in this increasingly important area; SVD based image processing in the future research.

Abstract: In this paper, we have developed a block cipher by modifying the Feistel cipher. In this, the plaintext is taken in the form of a pair of matrices. In one of the relations of encryption the plaintext is multiplied with the key matrix on both the sides. Consequently, we use the modular arithmetic inverse of the key matrix in the process of decryption. The cryptanalysis carried out in this investigation, clearly indicates that the cipher is a strong one, and it cannot be broken by any attack.

Abstract: In this investigation, we have modified the Feistel cipher by taking the plaintext in the form of a pair of square matrices. Here we have introduced the operation multiplication with the key matrices and the modular arithmetic addition in encryption. The modular arithmetic inverse of the key matrix is introduced in decryption. The cryptanalysis carried out in this paper clearly indicate that this cipher cannot be broken by the brute force attack and the known plaintext attack.

Abstract: A smart grid delivers power around the country and has an intelligent monitoring system, which not only keeps track of all the energy coming in from diverse sources but also can detect where energy is needed through a two-way communication system that collects data about how and when consumers use power. It is safer in many ways, compared with the current one-directional power supply system that seems susceptible to either sabotage or natural disasters, including being more resistant to attack and power outages. In such an autonomic and advanced-grid environment, investing in a pilot study and knowing the nation’s readiness to adopt a smart grid absolves the government of complex intervention from any failure to bring Japan into the autonomic-grid environment. This paper looks closely into the concept of the Japanese government’s ‘go green’ effort, the objective of which is to make Japan a leading nation in environmental and energy sustainability through green innovation, such as creating a low-carbon society and embracing the natural grid community. This paper paints a clearer conceptual picture of how Japan’s smart grid effort compares with that of the US. The structure of Japan’s energy sources is describe including its major power generation plants, photovoltaic power generation development, and a comparison of energy sources between Japan and the US. Japan’s smart community initiatives are also highlighted, illustrating the Japanese government planned social security system, which focuses on a regional energy management system and lifestyle changes under such an energy supply structure. This paper also discusses Japan’s involvement in smart grid pilot projects for development and investment, and its aim of obtaining successful outcomes. Engagement in the pilot projects is undertaken in conjunction with Japan’s attempt to implement a fully smart grid city in the near future. In addition, major smart grid awareness activities promotion bodies in Japan are discuss in this paper because of their important initiatives for influencing and shaping policy, architecture, standards, and traditional utility operations. Implementing a smart grid will not happen quickly, because when Japan does adopt one, it will continue to undergo transformation and be updated to support new technologies and functionality.

Abstract: The role of Information and Communication Technology in achieving organization’s strategic development goals has been an area of constant debate, and as well perceived in different management dimensions. Most universities are therefore employing it (ICT) as a tool for competitive advantage to support the accomplishment of their objectives. Universities are also known to have branches or campuses that need strong and steady strategic plans to facilitate their steady expansion and growth. Besides, production of quality services from the various levels of management in these universities requires quality strategic plans and decisions. In addition, to realize the steady growth and competitive advantage, ICT not only has to be an additive but a critical component towards supporting management processes in the universities. This research sought to determine the role of ICT in supporting management processes in institutions of higher learning in Kenya. The research investigated how the different levels of management used ICT in their management processes and whether the use had any effect on management processes. The research further made recommendations to the universities on better use of ICTs in their management processes. A public university in Kenya was used as a case study in this research.

Abstract: The energy demand in the enterprise market segment demands a supply format that accommodates all generation and storage options with active participation by end users in demand response. Basically, with today’s high power computing (HPC), a highly reliable, scalable, and cost effective energy solution that will satisfy power demands and improve environmental sustainability will have a broad acceptance. In a typical enterprise data center, power managment is a major challenge impacting server density and the total cost of ownership (COO). Storage uses a significant fraction of the power budget and there are no widely deployed power-saving solutions for enterprise storage systems. This work presents Data Center Networks (DCNs) for efficient power management in the context of SMART Grids. A SMART DCN is modelled with OPNET 14.5 for Network, Process and Node models. Also, an Extended SMART Integration Module in the context of SMART DCN is shown to be more cost effective than the traditional distribution grid in DCNs. The implementation challenges are discussed also. This paper suggests that smartening the grid for DCN will guarantee a sustainable energy future for the enterprise segments.

Abstract: This paper presents a novel approach to recognize Grantha, an ancient script in South India and converting it to Malayalam, a prevalent language in South India using online character recognition mechanism. The motivation behind this work owes its credit to (i) developing a mechanism to recognize Grantha script in this modern world and (ii) affirming the strong connection among Grantha and Malayalam. A framework for the recognition of Grantha script using online character recognition is designed and implemented. The features extracted from the Grantha script comprises mainly of time-domain features based on writing direction and curvature. The recognized characters are mapped to corresponding Malayalam characters. The framework was tested on a bed of medium length manuscripts containing 9-12 sample lines and printed pages of a book titled Soundarya Lahari writtenin Grantha by Sri Adi Shankara to recognize the words and sentences. The manuscript recognition rates with the system are for Grantha as 92.11%, Old Malayalam 90.82% and for new Malayalam script 89.56%. The recognition rates of pages of the printed book are for Grantha as 96.16%, Old Malayalam script 95.22% and new Malayalam script as 92.32% respectively. These results show the efficiency of the developed system.

Abstract: Learning Object Technology is a diverse and contentious area, which is constantly evolving, and will inevitably play a major role in shaping the future of both teaching and learning. Learning Objects are small chunk of materials which acts as basic building blocks of this technology enhanced learning and education. Learning Objects are hosted by various repositories available online so that different users can use them in multiple contexts as per their requirements. The major bottleneck for end users is finding an appropriate learning object in terms of content quality and usage. Theorist and researchers have advocated various approaches for evaluating learning objects in form of evaluation tools and metrics, but all these approaches are either qualitative based on human review or not supported by empirical evidence. The main objective of this paper is to study the impact of current evaluation tools and metrics on quality of learning objects and propose a new quantitative system LOQES that automatically evaluates the learning object in terms of defined parameters so as to give assurance regarding quality and value.

Abstract: To effectively support communication in such a dynamic networking environment as the ad hoc networks, the routing mechanisms should adapt to secure and trusted route discovery and service quality in data transmission. In this context, the paper proposed a routing protocol called Node Centric Trust based Secure Hybrid Routing Protocol [FHC-NCTSR] that opted to fixed hash chaining for data transmission and node centric trust strategy for secure route discovery. The route discovery is reactive in nature, in contrast to this, data transmission is proactive, hence the protocol FHC-NCTSR termed as hybrid routing protocol. The performance results obtained from simulation environment concluding that due to the fixed hash chaining technique opted by FHC-NCTSR, it is more than one order of magnitude faster than other hash chain based routing protocols such as SEAD in packet delivery. Due to the node centric strategy of route discovery that opted by FHC-NCTSR, it elevated as trusted one against to Rushing, Routing table modification and Tunneling attacks, in contrast other protocols failed to provide security for one or more attacks listed, example is ARIADNE that fails to protect from tunneling attack.

Abstract: Method for geophysical parameter estimations with microwave radiometer data based on Simulated Annealing: SA is proposed. Geophysical parameters which are estimated with microwave radiometer data are closely related each other. Therefore simultaneous estimation makes constraints in accordance with the relations. On the other hand, SA requires huge computer resources for convergence. In order to accelerate convergence process, oscillated decreasing function is proposed for cool down function. Experimental results show that remarkable improvements are observed for geophysical parameter estimations.

Abstract: In this paper, we present a task allocation model for search and rescue persons with disabilities in case of disaster. The multi agent-based simulation model is used to simulate the rescue process. Volunteers and disabled persons are modeled as agents, which each have their own attributes and behaviors. The task of volunteers is to help disabled persons in emergency situations. This task allocation problem is solved by using combinatorial auction mechanism to decide which volunteers should help which disabled persons. The disaster space, road network, and rescue process are also described in detail. The RoboCup Rescue simulation platform is used to present proposed model with different scenarios.

Abstract: A new method for image clustering with density maps derived from Self-Organizing Maps (SOM) is proposed together with a clarification of learning processes during a construction of clusters. It is found that the proposed SOM based image clustering method shows much better clustered result for both simulation and real satellite imagery data. It is also found that the separability among clusters of the proposed method is 16% longer than the existing k-mean clustering. It is also found that the separability among clusters of the proposed method is 16% longer than the existing k-mean clustering. In accordance with the experimental results with Landsat-5 TM image, it takes more than 20000 of iteration for convergence of the SOM learning processes.

Abstract: The Traveling salesman problem (TSP) is to find a tour of a given number of cities (visiting each city exactly once) where the length of this tour is minimized. Testing every possibility for an N city tour would be N! Math additions. Genetic algorithms (GA) and Memetic algorithms (MA) are a relatively new optimization technique which can be applied to various problems, including those that are NPhard. The technique does not ensure an optimal solution, however it usually gives good approximations in a reasonable amount of time. They, therefore, would be good algorithms to try on the traveling salesman problem, one of the most famous NP-hard problems. In this paper I have proposed a algorithm to solve TSP using Genetic algorithms (GA) and Memetic algorithms (MA) with the crossover operator Edge Assembly Crossover (EAX) and also analyzed the result on different parameter like group size and mutation percentage and compared the result with other solutions.

Abstract: In this paper we present a hybrid approach based on combining fuzzy k-means clustering, seed region growing, and sensitivity and specificity algorithms to measure gray (GM) and white matter (WM) tissue. The proposed algorithm uses intensity and anatomic information for segmenting of MRIs into different tissue classes, especially GM and WM. It starts by partitioning the image into different clusters using fuzzy k-means clustering. The centers of these clusters are the input to the region growing (SRG) method for creating the closed regions. The outputs of SRG technique are fed to sensitivity and specificity algorithm to merge the similar regions in one segment. The proposed algorithm is applied to challenging applications: gray matter/white matter segmentation in magnetic resonance image (MRI) datasets. The experimental results show that the proposed technique produces accurate and stable results.

Abstract: The geospatial analyst is required to apply art, science, and technology to measure relative positions of natural and man-made features above or beneath the earth’s surface, and to present this information either graphically or numerically. The reference positions for these measurements need to be well archived and managed to effectively sustain the activities in the spatial industry. The research herein described highlights the need for an information system for the Land Surveyor’s Equipment Store. Such a system is a database management system with a user-friendly graphical interface. This paper describes one such system that has been developed for the Equipment Store of the Department of Geomatic Engineering, Kwame Nkrumah University of Science and Technology (KNUST), Ghana. The system facilitates efficient management and location of instruments, as well as easy location of beacons together with their attribute information; it provides multimedia information about instruments in an Equipment Store. Digital camera was used capture the pictorial descriptions of the beacons. A Geographic Information System (GIS) software was employed to visualize the spatial location of beacons and to publish the various layers for the Graphical User Interface (GUI). The aesthetics of the interface was developed with user interface design tools and coded by programming. The developed Suite, powered by a reliable and fully scalable database, provides an efficient way of booking and analyzing transactions in an Equipment Store.

Abstract: A method of GA: Genetic Algorithm based ISODATA clustering is proposed.GA clustering is now widely available. One of the problems for GA clustering is a poor clustering performance due to the assumption that clusters are represented as convex functions. Well known ISODATA clustering has parameters of threshold for merge and split. The parameters have to be determined without any assumption (convex functions). In order to determine the parameters, GA is utilized. Through comparatives studies between with and without parameter estimation with GA utilizing well known UCI Repository data clustering performance evaluation, it is found that the proposed method is superior to the original ISODATA and also the other conventional clustering methods.

Abstract: The recent digital transmission systems impose the application of channel equalizers with bandwidth efficiency, which mitigates the bottleneck of intersymbol interference for high-speed data transmission-over communication channels. This leads to the exploration of blind equalization techniques that do not require the use of a training sequence. Blind equalization techniques however suffer from computational complexity and slow convergence rate. The Constant Modulus Algorithm (CMA) is a better technique for blind channel equalization. This paper examined three different error functions for fast convergence and proposed an adaptive blind equalization algorithm with variable step size based on CMA criterion. A comparison of the existing and proposed algorithms’ speed of convergence shows that the proposed algorithm outperforms the other algorithms. The proposed algorithm can suitably be employed in blind equalization for rapidly changing channels as well as for high data rate applications.

Abstract: This paper analyzes the throughput performance of IEEE 802.11b Wireless Local Area Network (WLAN) with one access point. The IEEE 802.11b is a wireless protocol standard. In this paper, a wireless network was established which has one access point. OPNET IT Guru Simulator (Academic edition) was used to simulate the entire network. Thus the effects of varying some network parameters such as the data-rate, buffer-sizes, and fragmentation threshold were observed on the throughput performance metric. Several simulation graphs were obtained and used to analyze the network performance.

Abstract: The rate of change in business and government
is accelerating. A number of techniques for addressing
that change have emerged independently to provide for
automated solutions in this environment. This paper will
examine three of the most popular of these technologies—
business process management, the agile software development
movement, and infrastructure virtualization—
to expose the commonalities in these approaches and
how, when used together, their combined effect results in
rapidly deployed, more successful solutions.